IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i6p1371-d1355906.html
   My bibliography  Save this article

A Multi-Criteria Decision-Making Framework for Zero Emission Vehicle Fleet Renewal Considering Lifecycle and Scenario Uncertainty

Author

Listed:
  • Giuseppe Aiello

    (Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Salvatore Quaranta

    (Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Rosalinda Inguanta

    (Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Antonella Certa

    (Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Mario Venticinque

    (CNR-ISAFoM Istituto per i Sistemi Agricoli e Forestali del Mediterraneo, 87036 Rende, Italy)

Abstract

In the last decade, with the increased concerns about the global environment, attempts have been made to promote the replacement of fossil fuels with sustainable sources. For transport, which accounts for around a quarter of total greenhouse gas emissions, meeting climate neutrality goals will require replacing existing fleets with electric or hydrogen-propelled vehicles. However, the lack of adequate decision support approach makes the introduction of new propulsion technologies in the transportation sector a complex strategic decision problem where distorted non-optimal decisions may easily result in long-term negative effects on the performance of logistic operators. This research addresses the problem of transport fleet renewal by proposing a multi-criteria decision-making approach and takes into account the multiple propulsion technologies currently available and the objectives of the EU Green Deal, as well as the inherent scenario uncertainty. The proposed approach, based on the TOPSIS model, involves a novel decision framework referred to as a generalized life cycle evaluation of the environmental and cost objectives, which is necessary when comparing green and traditional propulsion systems in a long-term perspective to avoid distorted decisions. Since the objective of the study is to provide a practical methodology to support strategic decisions, the framework proposed has been validated against a practical case referred to the strategic fleet renewal decision process. The results obtained demonstrate how the decision maker’s perception of the technological evolution of the propulsion technologies influences the decision process, thus leading to different optimal choices.

Suggested Citation

  • Giuseppe Aiello & Salvatore Quaranta & Rosalinda Inguanta & Antonella Certa & Mario Venticinque, 2024. "A Multi-Criteria Decision-Making Framework for Zero Emission Vehicle Fleet Renewal Considering Lifecycle and Scenario Uncertainty," Energies, MDPI, vol. 17(6), pages 1-19, March.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1371-:d:1355906
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/6/1371/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/6/1371/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guannan He & Dharik S. Mallapragada & Abhishek Bose & Clara F. Heuberger & Emre Genc{c}er, 2021. "Sector coupling via hydrogen to lower the cost of energy system decarbonization," Papers 2103.03442, arXiv.org.
    2. Li, Mengyu & Zhang, Xiongwen & Li, Guojun, 2016. "A comparative assessment of battery and fuel cell electric vehicles using a well-to-wheel analysis," Energy, Elsevier, vol. 94(C), pages 693-704.
    3. Jutta Geldermann & Otto Rentz, 2005. "Multi‐criteria Analysis for Technique Assessment:Case Study from Industrial Coating," Journal of Industrial Ecology, Yale University, vol. 9(3), pages 127-142, July.
    4. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Total cost of ownership, payback, and consumer preference modeling of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 103(C), pages 488-506.
    5. Ralph L. Keeney, 1974. "Multiplicative Utility Functions," Operations Research, INFORMS, vol. 22(1), pages 22-34, February.
    6. Wu, Geng & Inderbitzin, Alessandro & Bening, Catharina, 2015. "Total cost of ownership of electric vehicles compared to conventional vehicles: A probabilistic analysis and projection across market segments," Energy Policy, Elsevier, vol. 80(C), pages 196-214.
    7. Burke, Andrew & Sinha, Anish Kumar, 2020. "Technology, Sustainability, and Marketing of Battery Electric and Hydrogen Fuel Cell Medium-Duty and Heavy-Duty Trucks and Buses in 2020-2040," Institute of Transportation Studies, Working Paper Series qt7s25d8bc, Institute of Transportation Studies, UC Davis.
    8. Igor Linkov & Dmitriy Burmistrov, 2003. "Model Uncertainty and Choices Made by Modelers: Lessons Learned from the International Atomic Energy Agency Model Intercomparisons," Risk Analysis, John Wiley & Sons, vol. 23(6), pages 1297-1308, December.
    9. Davis, Brian A. & Figliozzi, Miguel A., 2013. "A methodology to evaluate the competitiveness of electric delivery trucks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 8-23.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Makena Coffman & Paul Bernstein & Sherilyn Wee, 2017. "Electric vehicles revisited: a review of factors that affect adoption," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 79-93, January.
    2. Coffman, Makena & Bernstein, Paul & Wee, Sherilyn, 2017. "Integrating electric vehicles and residential solar PV," Transport Policy, Elsevier, vol. 53(C), pages 30-38.
    3. Palmer, Kate & Tate, James E. & Wadud, Zia & Nellthorp, John, 2018. "Total cost of ownership and market share for hybrid and electric vehicles in the UK, US and Japan," Applied Energy, Elsevier, vol. 209(C), pages 108-119.
    4. Tushar Gahlaut & Gourav Dwivedi, 2024. "A Comprehensive Study for Multi-Criteria Comparison of EV, ICEV, and HEV," Papers 2404.11705, arXiv.org, revised Jun 2024.
    5. Saccani, Nicola & Perona, Marco & Bacchetti, Andrea, 2017. "The total cost of ownership of durable consumer goods: A conceptual model and an empirical application," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 1-13.
    6. Diao, Qinghua & Sun, Wei & Yuan, Xinmei & Li, Lili & Zheng, Zhi, 2016. "Life-cycle private-cost-based competitiveness analysis of electric vehicles in China considering the intangible cost of traffic policies," Applied Energy, Elsevier, vol. 178(C), pages 567-578.
    7. Lee, Yongseung & Kim, Chongman & Shin, Juneseuk, 2016. "A hybrid electric vehicle market penetration model to identify the best policy mix: A consumer ownership cycle approach," Applied Energy, Elsevier, vol. 184(C), pages 438-449.
    8. Ranjit R. Desai & Eric Hittinger & Eric Williams, 2022. "Interaction of Consumer Heterogeneity and Technological Progress in the US Electric Vehicle Market," Energies, MDPI, vol. 15(13), pages 1-25, June.
    9. Moon, Saedaseul & Lee, Deok-Joo, 2019. "An optimal electric vehicle investment model for consumers using total cost of ownership: A real option approach," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    10. Jones, J. & Genovese, A. & Tob-Ogu, A., 2020. "Hydrogen vehicles in urban logistics: A total cost of ownership analysis and some policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    11. Nienhueser, Ian Andrew & Qiu, Yueming, 2016. "Economic and environmental impacts of providing renewable energy for electric vehicle charging – A choice experiment study," Applied Energy, Elsevier, vol. 180(C), pages 256-268.
    12. Toheed Ghandriz & Bengt Jacobson & Manjurul Islam & Jonas Hellgren & Leo Laine, 2021. "Transportation-Mission-Based Optimization of Heterogeneous Heavy-Vehicle Fleet Including Electrified Propulsion," Energies, MDPI, vol. 14(11), pages 1-43, May.
    13. Noll, Bessie & del Val, Santiago & Schmidt, Tobias S. & Steffen, Bjarne, 2022. "Analyzing the competitiveness of low-carbon drive-technologies in road-freight: A total cost of ownership analysis in Europe," Applied Energy, Elsevier, vol. 306(PB).
    14. Breetz, Hanna L. & Salon, Deborah, 2018. "Do electric vehicles need subsidies? Ownership costs for conventional, hybrid, and electric vehicles in 14 U.S. cities," Energy Policy, Elsevier, vol. 120(C), pages 238-249.
    15. Hao, Xu & Lin, Zhenhong & Wang, Hewu & Ou, Shiqi & Ouyang, Minggao, 2020. "Range cost-effectiveness of plug-in electric vehicle for heterogeneous consumers: An expanded total ownership cost approach," Applied Energy, Elsevier, vol. 275(C).
    16. Seunghoon Lee & Young Hoon Lee & Yongho Choi, 2019. "Project Portfolio Selection Considering Total Cost of Ownership in the Automobile Industry," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
    17. Malima, Gabriel Clement & Moyo, Francis, 2023. "Are electric vehicles economically viable in sub-Saharan Africa? The total cost of ownership of internal combustion engine and electric vehicles in Tanzania," Transport Policy, Elsevier, vol. 141(C), pages 14-26.
    18. Piotr Wróblewski & Wojciech Lewicki, 2021. "A Method of Analyzing the Residual Values of Low-Emission Vehicles Based on a Selected Expert Method Taking into Account Stochastic Operational Parameters," Energies, MDPI, vol. 14(21), pages 1-24, October.
    19. Trost, Tobias & Sterner, Michael & Bruckner, Thomas, 2017. "Impact of electric vehicles and synthetic gaseous fuels on final energy consumption and carbon dioxide emissions in Germany based on long-term vehicle fleet modelling," Energy, Elsevier, vol. 141(C), pages 1215-1225.
    20. Alp, Osman & Tan, Tarkan & Udenio, Maximiliano, 2022. "Transitioning to sustainable freight transportation by integrating fleet replacement and charging infrastructure decisions," Omega, Elsevier, vol. 109(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1371-:d:1355906. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.